There is a data literacy issue – even around the name. Some people associate data with their phones (as a cost), others switch off as soon as numbers are involved. Awareness is also an issue, even amongst charities. The labelling of things — “open data”, “big data” — puts people off. Could we make the data more accessible to ordinary people? Do we need to do more on that.

However, this depends on the community. Some specialist groups are highly data literate, but they struggle to find the open data they need. Less data-literate communities soften don’t have it on their radar in the first place – they’d never think to look for it. There’s a role for intervention there. Data is not, in of itself, a solution, but it has a role in working towards a solution.

Some people see data as a problem — GDPR has exacerbated that — and so you have to engage them by making the data relevant to them. You can de-risk people’s adoption of data by making their adoption of data easier, and you can only do that by embedding yourself in their world, and making it an ingredient in their mission.

One approach is to listen out for problems organisations have, and then give them examples of how you have helped other organisations with similar issues using data. Data, and “digital” in particular is getting sexy in the charity sector right now – so there’s an opening there. DataKind has a network of 2000 data scientists supporting them, but they’re not inundated with requests – they still need to go and find people to get involved with.

There are sensitivities around some issues – like refugee organisations being wary of data sharing. Data literacy can ease these. But let’s be careful about the idea of “date literacy” – it’s not just about literacy, it’s about engagement and context. The whole idea of data literacy can be challenged. There are vocabulary gaps and conceptual gaps.

Sometimes you can use less abstract terms – “maps” rather than “GIS data”. Domain-driven design is a process of adapting your language to what your community are using.

Crossing a technical threshold

Up until recently, to be in the data game, you needed a certain level of technical competence. We’re building a player that makes data as accessible to everyone as we can. There’s a parallel with email, which once upon a time you needed the skill to compile SendMail before you could use it.

There are people working with filing card datasets which would never think of them as data. People use the tools they are familiar with, be it Excel or Photoshop. Some of the solution is showing them better ways of doing things.

We’re driving towards the unholy design of data nerds and service designers: look at Google Maps.

Beware of “poverty safaris” – diving into communities, telling them what to do and leaving. People get tired of endless studies and reports, but with no real changes off the back of it.

The experience of the Learning Academy at Aberdeen City Council – is that people will work with you, but it tales tome. Sometimes the data quality is extremely bad, though, which creates problems.

One solution? Using the PowerBI business intelligence tool – pull data from Excel spreadsheets and create data visualisation